code: def open_hdf5_s3(
      s3_url: str, *, block_size: int = 8388608
  ) -> HDF5Group:
      """Uses ``fsspec`` module to open the HDF5 file at ``s3_url``.
  
      This requires both ``fsspec`` and ``aiohttp`` to be installed.
  
      Args:
          s3_url: URL of dataset file in S3
          block_size: Number of bytes to fetch per read operation. Larger values
              may improve performance for large datasets
      """
  
      # Tells fsspec to fetch data in 8MB chunks for faster loading
      memory_cache_args = {
          "cache_type": "mmap",
          "block_size": block_size,
      }
      fs = fsspec.open(s3_url, **memory_cache_args)
  
      return h5py.File(fs.open())
  
file_path: pennylane/pennylane/data/base/hdf5.py
imports: from collections.abc import MutableMapping
  from pathlib import Path
  from typing import Literal, TypeVar, Union
  from uuid import uuid4
  from numpy.typing import ArrayLike
  from ._lazy_modules import fsspec, h5py
label_desc: Use image node_id 5 for calling a global function with example usage: open_hdf5_s3(s3_url) and returns: h5py